Improved Detection of Antibodies against SARS-CoV-2 by Microsphere-Based Antibody Assay

  1. Carol Ho-Yan Fong
  2. Jian-Piao Cai
  3. Thrimendra Kaushika Dissanayake
  4. Lin-Lei Chen
  5. Charlotte Yee-Ki Choi
  6. Lok-Hin Wong
  7. Anthony Chin-Ki Ng
  8. Polly K. P. Pang
  9. Deborah Tip-Yin Ho
  10. Rosana Wing-Shan Poon
  11. Tom Wai-Hin Chung
  12. Siddharth Sridhar
  13. Kwok-Hung Chan
  14. Jasper Fuk-Woo Chan
  15. Ivan Fan-Ngai Hung
  16. Kwok-Yung Yuen
  17. Kelvin Kai-Wang To

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Abstract

Currently available COVID-19 antibody tests using enzyme immunoassay (EIA) or immunochromatographic assay have variable sensitivity and specificity. Here, we developed and evaluated a novel microsphere-based antibody assay (MBA) for detecting immunoglobulin G (IgG) against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleoprotein (NP) and spike protein receptor binding domain (RBD). The seropositive cutoff value was set using a cohort of 294 anonymous serum specimens collected in 2018. The specificity was assessed using serum specimens collected from organ donors or influenza patients before 2020. Seropositive rate was determined among COVID-19 patients. Time-to-seropositivity and signal-to-cutoff (S/CO) ratio were compared between MBA and EIA. MBA had a specificity of 100% (93/93; 95% confidence interval (CI), 96–100%) for anti-NP IgG, 98.9% (92/93; 95% CI 94.2–100%) for anti-RBD IgG. The MBA seropositive rate for convalescent COVID-19 patients was 89.8% (35/39) for anti-NP IgG and 79.5% (31/39) for anti-RBD IgG. The time-to-seropositivity was shorter with MBA than EIA. MBA could better differentiate between COVID-19 patients and negative controls with higher S/CO ratio for COVID-19 patients, lower S/CO ratio with negative controls and fewer specimens in the equivocal range. MBA is robust, simple and is suitable for clinical microbiology laboratory for the accurate determination of anti-SARS-CoV-2 antibodies for diagnosis, serosurveillance, and vaccine trials.

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  1. Version published to 10.3390/ijms21186595
  2. ScreenIT

    SciScore for 10.1101/2020.05.26.20113191: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study has been approved by the HKU/HA HKW Institutional Review Board (UW 13-265 and UW 18-141).
    Consent: Written informed consent was obtained from all COVID-19 patients.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    v10.6.2 (FlowJo LLC, Ashland, OR, USA)
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Limitations of this study: First, we only recruited adult patients. Further evaluation should be performed in pediatric patients. Second, as for all serology assays, cross-reactivity may affect the results 9. Even for the pre-pandemic serum, some samples can be seropositive for SARS-CoV-2 because of cross reaction with other human coronaviruses, especially from lineage B betacoronavirus. Third, samples were not tested for virus neutralization and therefore neutralizing activities of the detected IgG antibodies are unknown.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a protocol registration statement.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.05.26.20113191 on medRxiv